A Study of a Simultaneous Multithreaded Processor Implementation
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Energy-Aware Partitioning for Multiprocessor Real-Time Systems
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Power-aware QoS Management in Web Servers
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
Energy-Aware Task Allocation for Rate Monotonic Scheduling
RTAS '05 Proceedings of the 11th IEEE Real Time on Embedded Technology and Applications Symposium
A Dynamic Compilation Framework for Controlling Microprocessor Energy and Performance
Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture
Predictable Performance in SMT Processors: Synergy between the OS and SMTs
IEEE Transactions on Computers
Energy-Efficient Real-Time Task Scheduling for a DVS System with a Non-DVS Processing Element
RTSS '06 Proceedings of the 27th IEEE International Real-Time Systems Symposium
Proceedings of the conference on Design, automation and test in Europe
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Increasing computational requirements are the cause of the use of multicore multithread processors in embedded real-time systems. Although these processors are more efficient they are also more complex and power hungry. Consequently energy consumption has become a major concern in these systems. In this context, new designs are being researched to deal with these limitations. On the other hand, simulators play an important role in research since they can reliably evaluate different research proposals. In this paper we propose some extensions for Multi2Sim, a multicore multithread processors simulator, in order to support hard real-time systems with dynamic voltage scaling capability. In addition, the main guidelines to model power-aware hard real-time systems are discussed, which will be useful to extend other processor simulators with similar purposes. Finally, different partitioning algorithms are also compared by using simulation experiments to show how they affect the system performance.